Tuesday, September 25, 2007



Page 96 of David Cox’s 2006 Principles of Statistical Inference has a very nice one-sentence summary of asymptotic theory:

[A]pproximations are derived on the basis that the amount of information is large, errors of estimation are small, nonlinear relations are locally linear and a central limit effect operates to induce approximate normality of log likelihood derivatives.



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